Abstract
The thermal control system (TCS) is an important constitution of payload racks. It takes away the waste heat generated by science experiments to maintain the temperature within the accepted range. TCSs consist of components like valves, fluid pipe lines, cold plates, pumps, controllers, and interfaces with Internal Active Thermal Control System (IATCS) of the space station. The payload temperature control is executed by automatic valve positioning and pump driving for flow via predefined command or crew laptop or ground workstation in real-time. The performance of a TCS, to a great extent, correlates to the health status of these components and the interactions between them. If one component falls in an abnormal condition, the TCS may fail to manage the payload thermal environment, causing a science experiment failure or even a safety incident. Therefore, it is significant to integrate the health monitoring capability into the TCS during the design process. Nevertheless, the failure mechanism of a TCS is complex due to that there exist dynamic interactions between system components, especially hardware (HW) and software (SW) interactions. It is reported insufficient to model such dynamic interactions using conventional reliability tools. Dynamic flowgraph methodology (DFM) is an advanced reliability modeling method, which can precisely describe the multi-valued component status and the dynamic interactions. TCS designer can get more accuracy of system failure modeling by using DFM. It can aid to the IHM design process in selecting test points, generating diagnosis strategy, events reporting etc. This paper firstly illustrates the TCS of payloads, which is followed by a brief introduction of the DFM technique. And then the TCS is modeled and analyzed, thus the DFM model and analytical results are applied in the integrated health monitoring (IHM) system design for TCS.
